A seismic survey represents an attempt to image or map the subsurface of the earth by sending sound energy down into the ground and recording the “echoes” that return from the rock layers below. The source of the down-going sound energy might come, for example, from explosions or seismic vibrators on land, or air guns in marine environments. During a seismic survey, the energy source is placed at various locations near the surface of the earth above a geologic structure of interest. Each time the source is activated, it generates a seismic (sound wave) signal that travels downward through the earth, is reflected, and, upon its return, is recorded at a great many locations on the surface. Multiple source/recording combinations are then combined to create a near continuous profile of the subsurface that can extend for many miles. In a two-dimensional (2-D) seismic survey, the recording locations are generally laid out along a single line, whereas in a three dimensional (3-D) survey the recording locations are distributed across the surface in a grid pattern. In simplest terms, a 2-D seismic line can be thought of as giving a cross sectional picture (vertical slice) of the earth layers as they exist directly beneath the recording locations. A 3-D survey produces a data “cube” or volume that is, at least conceptually, a 3-D picture of the subsurface that lies beneath the survey area. In reality, both 2-D and 3-D surveys interrogate some volume of earth lying beneath the area covered by the survey, and processing of the recorded data is then implemented to produce an interpretable image. Finally, a 4-D (or time-lapse) survey is one that is taken over the same subsurface target at two or more different times. This might be done for many reasons but often it is done to measure changes in subsurface reflectivity over time which might be caused by, for example, the progress of a water flood, movement of a gas/oil or oil/water contact, etc. Obviously, if successive images of the subsurface are compared any changes that are observed (assuming differences in the source signature, receivers, recorders, ambient noise conditions, etc., are accounted for) will be attributable to the progress of the subsurface processes that are at work.
A conventional seismic survey is composed of a very large number of individual seismic recordings or traces. These are typically 10 to 20 seconds long, to allow enough time for the echoes of interest to return before the source is fired again. Chapter 1, pages 9-89, of Seismic Data Processing by Ozdogan Yilmaz, Society of Exploration Geophysicists, 1987, contains general information relating to conventional 2-D processing and that disclosure is incorporated herein by reference. General background information pertaining to 3-D data acquisition and processing may be found in Chapter 6, pages 384-427, of Yilmaz, the disclosure of which is also incorporated herein by reference.
A conventional seismic trace is a digital recording of the acoustic energy reflecting from inhomogeneities or discontinuities in the subsurface, a partial reflection occurring each time there is a change in the elastic properties of the subsurface materials. The digital samples are usually acquired at 0.002 second (2 millisecond or “ms”) intervals, although 4 millisecond and 1 millisecond sampling intervals are also common. Each discrete sample in a conventional digital seismic trace is associated with a travel time, and in the case of reflected energy, a two-way travel time from the source to the reflector and back to the surface again, assuming, of course, that the source and receiver are both located on the surface. Many variations of the conventional source-receiver arrangement are used in practice, e.g. VSP (vertical seismic profiles) surveys, ocean bottom surveys, etc. Further, the surface location associated with every trace in a seismic survey is carefully tracked and is generally made a part of the trace itself (as part of the trace header information). This allows the seismic information contained within the traces to be later correlated with specific surface and subsurface locations, thereby providing a means for posting and contouring seismic data—and attributes extracted therefrom—on a map (i.e., “mapping”).
Conventional seismic acquisition and processing have advanced considerably over the previous decades, but the fundamental paradigm described above of recording “echoes” and using the timing of these to locate discontinuities in the Earth has remained essentially unchanged. Full-Waveform Inversion (FWI) is a time or frequency-based seismic processing technique that provides a more general paradigm for imaging subsurface structures: instead of relying solely on reflected or scattered waves echoing off of geological discontinuities in the Earth, FWI also makes use of transmitted/refracted waves that travel downwards, then turn to become horizontal, and finally turn upwards to emerge as upgoing seismic waves (possibly at a considerable distance from their origin). Subsurface structures in the Earth advance, retard, and/or distort these transmitted/refracted diving waves by their presence, and FWI solves for their location and properties from the characteristic imprints these leave in the data. See, for example, the teachings of Sirgue, et. al, in U.S. patent application Ser. No. 11/756,384, filed May 31, 2007, the disclosure of which is fully incorporated herein by reference as if set out at this point. FWI has recently moved from being an academic curiosity to finding widespread industrial application. See, for example, Sirgue, et. al, 2010, Full waveform inversion: the next leap forward in imaging at Valhall, First Break volume 28, page 65, the disclosure of which is fully incorporated herein by reference as if set out at this point.
Frequency-domain algorithms, in particular the FWI algorithm mentioned above, require input seismic data that are very different from what is conventionally recorded: they work on monochromatic wavefields. Conventional seismic data must be converted into a form these algorithms can use, by Fourier transformation from time to frequency domain (with appropriate windowing and tapering), after which individual frequencies are picked out for use. Sirgue's frequency-domain FWI algorithm detects subsurface structures by the perturbations they create in the amplitude and phase of these monochromatic wavefields.
Note the fundamental shift in paradigm here: instead of an impulsive source followed by listening for (recording) discrete returning echoes, mathematically for purposes of understanding the FWI algorithm the source may now be considered to be a continuous pure tone (i.e., a monochromatic source) exciting standing waves in the Earth. Unknown subsurface structures are detected by analyzing how the amplitude and phase of these standing waves differ from what was expected. By making use of transmitted/refracted diving waves, FWI can detect structures that do not generate a classic impulsive “echo”.
Thus, current practices when performing frequency-domain FWI on land vibrator (vibration) data are unnecessarily roundabout: seismic waves are generated using a swept-frequency source, the reflected/refracted waves are detected with a receiver, and the resulting data are then processed to approximate data from a traditional impulsive source. The “impulsive” seismic data are then processed to look like data from a monochromatic source, as needed by the frequency-domain inversion algorithms.
In fact, it has been shown that frequency-domain FWI only requires a small number of well-separated discrete frequencies in order to produce a good result. See, for example, Sirgue, L., and Pratt, R. G., 2004, Efficient waveform inversion and imaging: A strategy for selecting temporal frequencies, Geophysics volume 69, page 231, the disclosure of which is fully incorporated herein by reference as if set out at this point. Thus, with conventional acquisition followed by frequency-domain FWI, much of the energy produced by traditional broadband sources is wasted: it is at frequencies that are not used by the processing algorithm.
Note that, without low-frequency wide-offset data which contain the transmitted/refracted waves discussed above, full-waveform inversion often fails and may not resolve the subsurface structures (i.e. can produce a useless result). Unfortunately, traditional seismic sources do not provide the low-frequency waves that would generally be desired and, more particularly, the low-frequency data that may be used when full-waveform inversion is performed.
In particular, the most popular impulsive sources, dynamite on land or airguns offshore, produce relatively little low-frequency energy. The conventional way to provide more low-frequency energy for a seismic survey is to produce more energy at all frequencies, which is often impractical for cost, safety, and engineering considerations. Swept-frequency sources such as vibrators allow for more control of the frequencies of the emitted acoustic waves, and so may provide a more promising method for generating low-frequency waves.
Currently the practice for land vibrators is to generate a broadband sweep. The emitted vibrator source “chirp” is then correlated with the recorded seismic data to produce data traces that approximate those generated by an impulsive seismic source. Unfortunately, creating a reliable, high-output, broadband swept-frequency land vibrator has proven to be a challenge for low-frequency waves below about 3 Hz. Various solutions have been proposed, of which the most straightforward is to use a massive vibrator and to drive it with a nonlinear sweep such that the vibrator spends more time producing the lowest frequencies. See, for example, Baeten, in WO Patent Application 2010/037840 A1, filed Oct. 2, 2009, the disclosure of which is fully incorporated herein by reference as if set out at this point.
The situation is similar offshore. For swept-frequency marine sources (marine vibrators, resonators, water sirens, etc.) conventional practice is to generate a relatively broadband sweep. The emitted source “chirp” is then correlated with the recorded seismic data to produce a seismic trace that is conceptually equivalent to one generated by an impulsive seismic source such as an airgun (but without the airgun's production of seismic energy at frequencies above about 100 Hz that are not used for seismic imaging). Creating a reliable, high-output, broadband swept-frequency source for marine use has proven to be a challenge, particularly for frequencies lower than those that conventional airguns can generate (e.g. frequencies of about 4 Hz or less).
Thus, if the goal is to acquire data associated with low-frequency reflected/refracted waves for frequency-domain FWI or other uses, current industry practice has several disadvantages. As was discussed above, frequency-domain FWI performed on conventionally acquired broadband seismic data discards much of the generated data, and much of the energy produced by the source is thus wasted (whether from an impulsive or a swept-frequency source), which is obviously inefficient.
Potentially more troublesome, use of impulsive broadband sources introduces approximations that may degrade the final result. Frequency-domain full-waveform inversion uses a theory based on monochromatic standing-wave patterns. Frequency-domain FWI algorithms such as those discussed supra achieve computational practicality by approximating these source-excited wavefields using tapered monochromatic sine-wave sources modeled in the time domain. The resulting data are then discrete-Fourier-transformed and a single frequency extracted. The recorded broadband field data are similarly discrete-Fourier-transformed and the same single frequency extracted. The inversion process then attempts to find an Earth model that best matches the amplitude and/or phase of the modeled monochromatic data with the amplitude and/or phase derived from the recorded impulsive broadband data for that frequency. The tapered-monochromatic sources used in computer modeling typically have a very different signature than the broadband sources used in the field. This introduces an approximation, which is only partly ameliorated by the step of Fourier-transforming both the real and modeled data and extracting the same single frequency.
The goal of an inversion algorithm is to produce a computer model of subsurface structures that correctly predicts the subsurface structures of interest in the real Earth. Logically, the better the computer modeling of how the waves are generated, recorded, and processed matches what happened in the real Earth, the better the result of the inversion algorithm can be. To produce a better inversion result, it is desirable to match the acquisition and processing of the seismic data and the computational modeling in the computer as closely as practicable. This can be achieved by modifying the computer modeling to better match what happened in the real Earth. It could also be achieved by modifying the acquisition and processing of the field data to match the computer modeling.
Finally, in addition to all these shortcomings of existing practice, conventional seismic sources often do not produce sufficient energy over the time duration of a conventional seismic trace to generate low-frequency transmitted/refracted diving waves recordable at the very wide offsets desirable for full-waveform inversion.
Typically, the trace lengths used in existing seismic surveys are based on the limitations of a conventional imaging paradigm that frequency-domain FWI does not use. Without being limited by theory, the monochromatic standing waves used by a frequency-domain algorithm repeat endlessly. Data generated by a monochromatic source do not have a natural maximum recording length beyond which no further useful data can be received. Accordingly, the signal-to-noise ratio may be increased by obtaining signals over a longer duration by allowing the sources to radiate for longer time periods.
Existing methods for using very long sweeps to generate more energy from low-amplitude sources require sources with precisely controllable emitted waveforms. See for example Meunier, U.S. Pat. No. 6,714,867 B2, filed Feb. 9, 2001, the disclosure of which is fully incorporated herein by reference as if set out at this point. Such control can be difficult to achieve in practice, especially at low frequencies.
Heretofore, as is well known in the seismic acquisition and processing arts, there has been a need for a system and method of efficiently acquiring low-frequency data optimized for use with inversion algorithms, particularly frequency-domain full-waveform inversion. Accordingly, it should now be recognized, as was recognized by the present inventors, that there exists, and has existed for some time, a very real need for a method of seismic data acquisition and processing that would address and solve the above-described problems.
Before proceeding to a description of the present invention, however, it should be noted and remembered that the description of the invention which follows, together with the accompanying drawings, should not be construed as limiting the invention to the examples (or preferred embodiments) shown and described. This is so because those skilled in the art to which the invention pertains will be able to devise other forms of this invention within the ambit of the appended claims. In particular, the acquisition methodology may prove useful for obtaining low frequencies for other algorithms besides frequency-domain full-waveform inversion, for example, time-domain full-waveform inversion.